code: def test_detokenization_in_fast_tokenizers(model_name):
      tokenizer = Tokenizer.load(
          pretrained_model_name_or_path=model_name, use_fast=True
      )
      for text in TEXTS:
          encoded = tokenizer.encode_plus(
              text, add_special_tokens=False
          ).encodings[0]
  
          detokenized = " ".join(encoded.tokens)
          detokenized = re.sub(r"(^|\s+)(##)", "", detokenized)
  
          detokenized_ids = tokenizer(
              detokenized, add_special_tokens=False
          )["input_ids"]
          detokenized_tokens = [
              tokenizer.decode([tok_id]).strip()
              for tok_id in detokenized_ids
          ]
  
          assert encoded.tokens == detokenized_tokens
  
file_path: FARM/test/test_tokenization.py
imports: import logging
  import pytest
  import re
  from transformers import BertTokenizer, BertTokenizerFast, RobertaTokenizer, RobertaTokenizerFast, XLNetTokenizer, XLNetTokenizerFast, ElectraTokenizerFast
  from tokenizers.pre_tokenizers import WhitespaceSplit
  from farm.modeling.tokenization import Tokenizer, tokenize_with_metadata, truncate_sequences
  import numpy
label_desc: Use image node_id 11 for calling a global function with example usage: test_detokenization_in_fast_tokenizers(model_name) without return types